Chemical Switching: A Concept Inspired by Strategies from Biocatalysis and Organocatalysis
Bibliographic record
Abstract
In this perspective the character of aldehyde functional groups is outlined as central intermediates in DNA repair. As highly reactive entities, aldehydes exist in limited quantities and in contextualized scenarios only and are commonly masked as a Schiff base. Recent advances reveal that principles of organic chemistry can modulate the enzymatic cleavage of Schiff bases, a process termed chemical switching. This approach not only enhances the production of canonical DNA repair products, bolstering cellular function, but also generates novel reaction intermediates, potentially rewiring cellular pathways. However, such rewiring could increase the complexity and toxicity of DNA repair intermediates, influencing therapeutic outcomes. To shape novel classes of therapeutics, an exploitation of these fine-tuned reaction principles requires expertise of enzymologists and scientists skilled in bio- and organocatalysis. Here, the current state of the art is outlined in chemically switching enzymatic function in cells with focus on DNA repair, highlighting challenges of this new type of protein modulation and discussing possible solutions. This paints a picture of the chemical switching concept as an emerging playing field with exciting translational prospects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".